Compound Drought and Heatwave (CDHW) Event Indicators – Adige River Catchment, 1950–2023

Science Case Name

Hot and dry compound events in the Adige River Catchment (Eastern Italian Alps)

Dataset Title

Compound Drought and Heatwave (CDHW) event indicators for the Adige River Catchment (1950-2023)

Dataset Description

Occurrence and severity gridded fields of CDHW events over the Adige River Catchment from 1950 to 2023. The dataset includes the event list with duration, extent, total severity, magnitude and ranking of each identified event.

Key Methodologies

A CDHW event is determined by the co-occurrence of drought and heatwave conditions over at least 60% of the Adige River Catchment. Drought and heatwave indicators were derived using daily temperature and precipitation data from the E-OBS gridded dataset.

A drought period is identified as a sequence of consecutive months with a negative Standardized Precipitation Index (SPI), starting with the first month where the SPI-6 (6-month timescale) falls below -1. Heatwaves are defined as periods of at least three consecutive days where the daily maximum temperature (TX) exceeds the 90th percentile for that specific calendar day, determined using a 31-day running mean centred on the day under evaluation and considering all values from 1950 to 2023. When two or more periods of consecutive exceedances are separated by one day with TX below the threshold, they are considered as a single heatwave occurrence and the day below the threshold is included in the event duration. 

In the occurrence grids, for each day in a CDHW event, grid cells where both drought and heatwave conditions are detected are flagged as "1". If the compound condition is not met, the cell is flagged as "0". In the severity fields, the severity (dimensionless) for each day in a CDHW event is calculated as the product of the standardized daily TX over the days of the event and the absolute value of SPI-6 in the corresponding month. The calculation of the severity is similar to the one proposed by Mukherjee and Mishra (2021), but with the percentiles used in the standardization of TX varying with the day of the year. 

The list of CDHW events affecting the Adige River Catchment over 1950-2023 includes the start and end dates, the percentage of the area affected, the total severity (dimensionless), magnitude (dimensionless) and ranking of the event. The total severity of the event is defined as the average of the CDHW severities of all grid cells in the catchment experiencing the CDHW conditions. The total severity of the CDHW event at each grid cell is calculated as the sum of the daily severity values over days flagged as "1". The magnitude is the product of the total severity and the fraction of area affected. CDHW events are ranked based on their magnitude.

Temporal Domain

1950-2023

Spatial Domain

Extended region centred on the Adige River Catchment (7.10°-15.30°E, 44.10°-49.10°N); Spatial resolution: 0.1°x0.1° (EPGS:4326)

Key Indicators

CDHW occurrence and severity (grid) and CDHW duration, extent, total severity and magnitude (list)

Data Format

netCDF and CSV

Source Data

E-OBS dataset (v29.0e)

Accessibility

Zenodo, https://doi.org/10.5281/zenodo.13839122  

Stakeholder Relevance

The list of hot and dry events for the Adige River Catchment can support regional water managers to identify the most critical meteorological conditions over the past decades and link them to the observed local impacts. The details about event severity, magnitude and spatial and temporal extent provided in the list can be used directly to characterize the impactful hot and dry episodes. Moreover, the gridded fields offer a consistent description of the phenomena throughout the Adige River Catchment and can be used to localize the affected areas and identify the main spatial patterns of hot and dry conditions.    

Limitations/Assumptions

Results accuracy can be influenced by potential biases in the original data source over the study area. The 0.1-grid of E-OBS limits a detailed representation of local conditions and spatial patterns, while the continuous temporal coverage enables historical event detection and analysis. Thresholds used in the proposed definitions are based on expert knowledge and other choices are also possible.

Contact Information

Elena Maines (Center for Climate Change and Transformation - Eurac Research) (data curator)

Alice Crespi (Center for Climate Change and Transformation - Eurac Research) (data curator)

Marc Lemus-Canovas (Center for Climate Change and Transformation - Eurac Research; Universidade de Santiago de Compostela) (data curator)